This description generally relates to identifying topics of content items, and particularly to developing and using machine learning models to predict topics of content items to be shared on an online system while they are being composed.
An online system allows its users to connect to and communicate with other users of the online system. Users may create user profiles on the online system that are tied to their identities and include information about the users, such as interests and demographic information. The users may be individuals or entities such as corporations or charities. Because of the increasing popularity of these types of online systems and the increasing amount of user-specific information maintained by such online systems, an online system provides an ideal forum for individuals or third parties to share different types of content.
A social networking system is one example of an online system that allows its users to post content to the social networking system for presentation to other social networking system users, allowing the users to interact with each other. Examples of content items include stories, photos, videos, and invitations. Additionally, the social networking system typically generates content items describing actions performed by users and identified by the social networking system. For example, a content item is generated when a user of a social networking system checks into a location, shares content posted by another user, or performs any other suitable interaction. The social networking system presents content items describing an action performed by a user to additional users connected to the user via the social networking system. Typically, the social networking system presents content items to users in a feed in an order based on times when content items are generated or received by the social networking system and also based on anticipated interest of the user in the content items.
Over time, users generate a large volume of content items that cover a variety of topics. For convenience, users often browse content items by topics. Tagging content items to topic tags promote their visibility to other users. Conventionally, topics tags are extracted from posts after the posts were submitted. However, users cannot update topic tags because the posts have already been published and possibly have been shared with others.